Optimizing with Analytics
Successful freemium apps have analytics built into the experience so that developers can understand user preferences and continually improve the apps.
“At Jam City we really value scale, and in order to achieve scale, you need to have the best user experience possible. We look at data as a tool that we can use to better improve that experience,” says Casertano. “What that means is taking a look at some very high-level KPIs, like retention, which is how many users are coming back to the app on a day-to-day basis. We don’t just look at short-term retention, we look at very, very long-term retention, because our goal is to create experiences that people play for years."
“Drilling down from retention, it’s really important to look at funnels — so how many players are moving from step to step — and an easy way to do that is to look at it in a linear game, through how many users are progressing from level to level. What this does is allows you to establish relationships between monetization and drop off. And that’s an area where you need to be really delicate and really expert in your tuning, because you want to create an experience that is challenging — because people find challenges fun — but you don’t want to create an experience that is too challenging — because people then get overwhelmed and frustrated by it. So the numbers allow us to do this on a continual basis and improve every day.”
At Originator, Ghazal looks at data to understand what users find most compelling. “We rely on analytics pretty heavily to learn, not just from a monetization perspective, but also where are they spending time in the app, what are the parts of the app that seem more interesting than others,” he says. “We’re already seeing surprises in the new Endless Learning Academy, where people are spending more time in a certain part of the app where we didn’t expect them to. And we’re not 100% sure why yet. Some of that is going to go into follow-up sessions with some of our users to try to understand what works and what doesn’t. But there are just as many surprises as there are things that we see that we expected to see.”
At VSCO, Chookaszian finds that pairing quantitative data with qualitative feedback helps to form a more meaningful picture of user preferences. “If you take a narrow view on quantitative analysis you can really miss the forest through the trees. So we can form a hypothesis from the data but then it’s really important to go out and validate that with the community.”